It is an important social goal to be able to accurately diagnose and treat mental disorders. However, for many of these disorders, tests such as x-rays, blood tests and tests for biomarkers are not helpful for their diagnosis. Therefore, clinicians must rely on other approaches to diagnose a disorder.
Clinicians use various approaches to assist them in the diagnosis of a disorder. However, these approaches have a number of limitations. For example, some solutions count the number of symptoms exhibited by a patient in order to determine whether the patient is suffering from a disorder. However, merely counting a number of symptoms does not take into account differences between the symptoms or different combinations of symptoms, and does not take into account differences within a symptom, such as a range of severities.
In addition, these solutions require the symptom count to exceed a threshold for the diagnosis of the disorder. Thus, as long as a patient exhibits a certain number of symptoms, no matter what those symptoms are, the patient may be diagnosed with the disorder. Further, if the symptom count is at or near this threshold, these solutions do not provide any further information to help the clinician with their diagnosis, leading to inconsistent diagnoses across clinicians.
Therefore, there exists ample opportunity for the improvement in the accuracy of the diagnosis of disorders.